66 citations · 72 across the 9 of their papers we have counts for
4 papers · 1 filter
PoFEL: Energy-efficient Consensus for Blockchain-based Hierarchical Federated Learning
Shengyang Li, Qin Hu, Zhilin Wang
Facilitated by mobile edge computing, client-edge-cloud hierarchical federated learning (HFL) enables communication-efficient model training in a widespread area but also incurs ad…
Straggler Mitigation and Latency Optimization in Blockchain-based Hierarchical Federated Learning
Zhilin Wang, Qin Hu, Minghui Xu +1
Cloud-edge-device hierarchical federated learning (HFL) has been recently proposed to achieve communication-efficient and privacy-preserving distributed learning. However, there ex…
Blockchain-based Edge Resource Sharing for Metaverse
Zhilin Wang, Qin Hu, Minghui Xu +1
Although Metaverse has recently been widely studied, its practical application still faces many challenges. One of the severe challenges is the lack of sufficient resources for com…
Resource Optimization for Blockchain-based Federated Learning in Mobile Edge Computing
Zhilin Wang, Qin Hu, Zehui Xiong
With the development of mobile edge computing (MEC) and blockchain-based federated learning (BCFL), a number of studies suggest deploying BCFL on edge servers. In this case, resour…